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Nitropyrene (1-NP) is a specific indicator of exposure to diesel exhaust and is partly metabolized to 1-aminopyrene (1-AP) and N-acetyl-1-aminopyrene (1-NAAP), which are excreted in urine. This study was conducted to evaluate the effects of gene polymorphisms of metabolic enzymes for 1-NP on the urinary concentrations of 1-AP and 1-NAAP. The study participants were 70 South Koreans who were occupationally or environmentally exposed to diesel exhaust. To evaluate 1-NP exposure levels, we sampled airborne particulate matters with a personal air sampler and measured urinary 1-AP and 1-NAAP concentrations. The genetic polymorphisms of the 1-NP metabolic enzymes (CYP1A1, CYP1B1, EPHX1, NQO1, and NAT2) were determined by direct sequencing. The mean 1-NP exposure level was 20.40 pg/m3, and the mean urinary concentrations of 1-AP and 1-NAAP were 0.074 nM and 0.213 nM, respectively. The correlation coefficient between the 1-NP exposure level and urinary 1-AP concentrations was 0.0138 and that between the 1-NP exposure level and urinary 1-NAAP concentrations was 0.1493, and neither correlation coefficient was statistically significant. The correlation coefficient between the 1-NP exposure level and urinary 1-AP concentrations showed statistically significant differences according to the CYP1A1 and CYP1B1 genotypes, and that between the 1-NP exposure level and urinary 1-NAAP concentrations was significantly different according to the CYP1A1, CYP1B1, and NAT2 genotypes. The urinary concentration of 1-NAAP is a better biomarker for exposure to 1-NP or DEPs because the former is higher, easier to measure, and more strongly correlated with 1-NP exposure levels than that of 1-AP. The relationship between 1-NP exposure and urinary 1-AP or 1-NAAP concentration depends on the single nucleotide polymorphism types of CYP1A1, CYP1B1, NQO1, and NAT2.

This study aimed to develop an English version of a doping drug-recognition system using deep learning-based optical character recognition (OCR) technology. A database of 336 banned substances was built based on the World Anti-Doping Agency’s International Standard Prohibited List and the Korean Pharmaceutical Information Center’s Drug Substance Information. For accuracy and validity analysis, 886 drug substance images, including 152 images of prescriptions and drug substance labels collected using data augmentation, were used. The developed hybrid system, based on the Tesseract OCR model, can be accessed by both a smartphone and website. A total of 5379 words were extracted, and the system showed character recognition errors regarding 91 words, showing high accuracy (98.3%). The system correctly classified all 624 images for acceptable substances, 218 images for banned substances, and incorrectly recognized 44 of the banned substances as acceptable. The validity analysis showed a high level of accuracy (0.95), sensitivity (1.00), and specificity (0.93), suggesting system validity. The system has the potential of allowing athletes who lack knowledge about doping to quickly and accurately check whether they are taking banned substances. It may also serve as an efficient option to support the development of a fair and healthy sports culture.

Groundwater is an important freshwater source that satisfies the needs of a significant portion of the world’s population, industries, and ecosystems [...]

Due to increased environmental pressures, significant research has focused on finding suitable biodegradable plastics to replace ubiquitous petrochemical-derived polymers. Polyhydroxyalkanoates (PHAs) are a class of polymers that can be synthesized by microorganisms and are biodegradable, making them suitable candidates. The present study looks at the degradation properties of two PHA polymers: polyhydroxybutyrate (PHB) and polyhydroxybutyrate-co-polyhydroxyvalerate (PHBV; 8 wt.% valerate), in two different soil conditions: soil fully saturated with water (100% relative humidity, RH) and soil with 40% RH. The degradation was evaluated by observing the changes in appearance, chemical signatures, mechanical properties, and molecular weight of samples. Both PHB and PHBV were degraded completely after two weeks in 100% RH soil conditions and showed significant reductions in mechanical properties after just three days. The samples in 40% RH soil, however, showed minimal changes in mechanical properties, melting temperatures/crystallinity, and molecular weight over six weeks. By observing the degradation behavior for different soil conditions, these results can pave the way for identifying situations where the current use of plastics can be replaced with biodegradable alternatives.

Background This study used various tools, including a self-assessment questionnaire, the Clinical Assessment of Driver-Related Skills (CADReS), and a driving simulation, to discriminate between older and non-older drivers. Methods We evaluated driving habits, driving-related health behaviors, and morbidities using a self-assessment questionnaire and examined visual, motor, and cognitive functions using the CADReS and a vehicle simulator of four junction scenarios that are typical of accidents involving older drivers. The areas under the receiver operating characteristic curves (AUCs) were calculated to compare the age-related discriminating ability of these tools between older (≥65 years) and non-older participants. Results Thirty of the 40 participants (75%) were older. Older drivers were slower than non-older drivers according to the rapid walking pace (8.0 vs. 6.1 seconds), and their cognitive function was poorer based on the trail-making test (117 vs. 51 seconds). While driving on the vehicle simulator, the rate of violating traffic rules was higher and the maximal velocity was slower in the older group than in the non-older group. The AUC values for CADReS and driving simulation outcomes ranged from 0.59 to 0.95, while the rapid walking pace, trail-making test, and velocity of the left turn at an acute junction in the dark showed high discriminatory power (AUC>0.9).Conclusions: The rapid walking pace and trail-making test in CADReS, as well as the driving simulation, were useful tools to discriminate between older and non-older drivers.

Abstract In addition to somatic mutations, germline genetic predisposition to hematologic malignancies is currently emerging as an area attracting high research interest. In this study, we investigated genetic alterations in Korean acute lymphoblastic leukemia/lymphoma (ALL) patients using targeted gene panel sequencing. To this end, a gene panel consisting of 81 genes that are known to be associated with 23 predisposition syndromes was investigated. In addition to sequence variants, gene-level copy number variations (CNVs) were investigated as well. We identified 197 somatic sequence variants and 223 somatic CNVs. The IKZF1 alteration was found to have an adverse effect on overall survival (OS) and relapse-free survival (RFS) in childhood ALL. We found recurrent somatic alterations in Korean ALL patients similar to previous studies on both prevalence and prognostic impact. Six patients were found to be carriers of variants in six genes associated with primary immunodeficiency disorder (PID). Of the 81 genes associated with 23 predisposition syndromes, this study found only one predisposition germline mutation (TP53) (1.1%). Altogether, our study demonstrated a low probability of germline mutation predisposition to ALL in Korean ALL patients.

Summary: Overwriting counterselectable markers is an efficient strategy for removing wild-type DNA or replacing it with payload DNA of interest. Currently, one bottleneck of efficient genome engineering in mammals is the shortage of counterselectable (negative selection) markers that work robustly without affecting organismal developmental potential. Here, we report a conditional Piga knockout strategy that enables efficient proaerolysin-based counterselection in mouse embryonic stem cells. The conditional Piga knockout cells show similar proaerolysin resistance as full (non-conditional) Piga deletion cells, which enables the use of a PIGA transgene as a counterselectable marker for genome engineering purposes. Native Piga function is readily restored in conditional Piga knockout cells to facilitate subsequent mouse development. We also demonstrate the generality of our strategy by engineering a conditional knockout of endogenous Hprt. Taken together, our work provides a new tool for advanced mouse genome writing and mouse model establishment.

Background: According to previous studies, low serum total cholesterol (TC) is associated with higher cancer incidence and mortality. However, the prognostic implications of preoperative TC in patients with gastric cancer (GC) remain to be determined. Methods: A total of 1251 patients with GC, who underwent radical gastrectomy between 2005 and 2008, were recruited. Propensity score weighting (PSW) based on a generalized boosted method (GBM) was used to control for selection bias. Results: After balancing the preoperative and operative covariates, low TC was associated with high incidence of complications (severe complication rate: 15.2% (Low TC) vs. 4.7% (Normal TC) vs 5.5% (High TC); p = 0.004). In multivariable analysis, lowering TC was associated with poor OS and RFS in weighted population. [OS: hazard ratio (HR) = 0.92; 95% CI = 0.867–0.980; P = 0.009 and RFS: HR = 0.93; 95% CI = 0.873–0.988; P = 0.02]. Conclusions: Preoperative TC is a useful predictor of postoperative survival and postoperative complications in patients with stage I–III GC and may help to identify high-risk patients for rational therapy, including nutritional support, and timely follow-up.

Groundwater is critical to the socioeconomic development of any region. Infiltration of surface water into the ground is influenced by a variety of factors such as soil pores, folds, fractures, faults, and joints, all of which contribute to groundwater recharge. Groundwater is an important source of freshwater in the drought-prone Pudukkottai district of Tamil Nadu, India. Therefore, the search for groundwater potential zones (GWPZs) is critical. The present study focuses on the investigation of potential groundwater zones using geospatial techniques. Geology, land use and land cover, geomorphology, soil, drainage density, lineament, and groundwater levels were obtained from state and non-state associations. ArcGIS version 10.8 was used to create all thematic layers and classified grids. The intensive use of groundwater in arid and semiarid regions is becoming a problem for the public to meet their freshwater needs. The condition of arid and semi-arid regions due to intensive groundwater extraction has become one of the most important environmental problems for the public. In this study, a powerful groundwater potential mapping technique was developed using integrated remote sensing data from GIS-AHP. Using AHP techniques, thematic layers for geology, geomorphology, and soil followed by drainage, drainage density and lineament, lineament density, slope, water level, and lithological parameters were created, classified, weighted, and integrated into a GIS environment. According to the results of the study, it is estimated that 14% of the groundwater potential in the study area is good, 49% is moderate and 36% is poor. A groundwater level map was used to verify the groundwater potential. In addition, the model was validated with a single-layer sensitivity analysis, which showed that geology was the most influential layer and water level was the least influential thematic layer. The low-potential areas identified on the groundwater potential map can be used for further study to identify ideal locations for artificial recharge. In low potential areas, the groundwater potential map can be used to find ideal locations for artificial recharge. The water table in the area must be raised by artificial recharge structures such as infiltration basins, recharge pits, and agricultural ponds. Artificial recharge structures such as infiltration basins, recharge pits, and agricultural ponds can be used for groundwater development in the low potential zones. The GWPZ map was successfully validated with three proxy data, such as the number of wells, groundwater level, and well density, obtained from well inventory information. The results of this study will improve our understanding of the geographic analysis of groundwater potential and help policy makers in this drought-prone area to create more sustainable water supply systems.

Block copolymers generally have peculiar morphological characteristics, such as strong phase separation. They have been actively applied to polymer electrolyte membranes for proton exchange membrane fuel cells (PEMFCs) to obtain well-defined hydrophilic regions and water channels as a proton pathway. Although molecular simulation tools are advantageous to investigate the mechanism of water channel formation based on the chemical structure and property relationships, classical molecular dynamics simulation has limitations regarding the model size and time scale, and these issues need to be addressed. In this study, we investigated the morphology of sulfonated block copolymers synthesized for PEM applications using a mesoscale simulation based on the dynamic mean-field density functional method, widely applied to investigate macroscopic systems such as polymer blends, micelles, and multi-block/grafting copolymers. Despite the similar solubility parameters of the monomers in our block-copolymer models, very different morphologies in our 3D mesoscale models were obtained. The model with sulfonated monomers, in which the number of sulfonic acid groups is twice that of the other model, showed better phase separation and water channel formation, despite the short length of its hydrophilic block. In conclusion, this unexpected behavior indicates that the role of water molecules is important in making PEM mesoscale models well-equilibrated in the mesoscale simulation, which results in the strong phase separation between hydrophilic and hydrophobic regions and the ensuing well-defined water channel. PEM synthesis supports the conclusion that using the sulfonated monomers with a high sulfonation degree (32.5 mS/cm) will be more effective than using the long hydrophilic block with a low sulfonation degree (25.2 mS/cm).

As the utilization of DC systems increases worldwide, the importance of DC cutoff technology is increasing. We proposed a hybrid DC cutoff technology combining an SFCL (superconducting fault-current-limiter) and a mechanical DC circuit breaker. This model can perform a fault-current-limiting operation through the quenching of the SFCL and a breaking operation through an artificial cutoff zero point of a mechanical DC circuit breaker. In particular, the SFCL is responsible for the growth of the initial fault current according to the DC characteristics. As the DC system’s supply and demand increase, the DC system’s capacity also increases. Therefore, the fault-current-limiting capability of the SFCL should be increased according to the increasing DC system breaking capacity. The fault-current-limiting capability can be increased by increasing the superconducting wires used in the SFCL. Current commercially available SFCLs use bifilar-helical-type and bifilar-spiral-type winding methods. These have the disadvantage of increased volume with increased capacity. To compensate for these disadvantages, we proposed a bifilar-meander-type winding method. In this paper, a new bifilar-meander-type winding method was introduced. In addition, the structural and electromagnetic parts of the existing winding method and the bifilar-meander-type winding method were compared and analyzed for differences. The program used for this analysis is the electromagnetic analysis Maxwell program. As a result, it was confirmed that the bifilar-meander-type winding method is superior to the conventional bifilar-helical and bifilar-spiral types.

Large-scale datasets, which have sufficient and identical quantities of data in each class, are the main factor in the success of deep-learning-based classification models for vision tasks. A shortage of sufficient data and interclass imbalanced data distribution, which often arise in the medical domain, cause modern deep neural networks to suffer greatly from imbalanced learning and overfitting. A diagnostic model of diabetic retinopathy (DR) that is trained from such a dataset using supervised learning is severely biased toward the majority class. To enhance the efficiency of imbalanced learning, the proposal of this study is to leverage retinal fundus images without human annotations by self-supervised or semi-supervised learning. The proposed approach to DR detection is to add an auxiliary procedure to the target task that identifies DR using supervised learning. The added process uses unlabeled data to pre-train the model that first learns features from data using self-supervised or semi-supervised learning, and then the pre-trained model is transferred with the learned parameter to the target model. This wrapper algorithm of learning from unlabeled data can help the model gain more information from samples in the minority class, thereby improving imbalanced learning to some extent. Comprehensive experiments demonstrate that the model trained with the proposed method outperformed the one trained with only the supervised learning baseline utilizing the same data, with an accuracy improvement of 4~5%. To further examine the method proposed in this study, a comparison is conducted, and our results show that the proposed method also performs much better than some state-of-the-art methods. In the case of EyePaCS, for example, the proposed method outperforms the customized CNN model by 9%. Through experiments, we further find that the models trained with a smaller but balanced dataset are not worse than those trained with a larger but imbalanced dataset. Therefore, our study reveals that utilizing unlabeled data can avoid the expensive cost of collecting and labeling large-scale medical datasets.

This study illustrated the potential applications of thermoresponsive poly(N-isopropylacrylamide) (PNIPAm) grafted nylon membranes with different grafting yields and grafting architecture. The thermoresponsive gating performance at temperatures below and above the lower critical solution temperature (LCST) of PNIPAm (32 °C) were demonstrated. The linear PNIPAm-grafted nylon membrane exhibited a sharp response over the temperature range 20–40 °C. The grafting yield of 25.5% and 21.9%, for linear and crosslinked PNIPAm respectively, exhibited highest thermoresponsive gating function for water flux and had a stable and repeatable “open-closed” switching function over 5 cycle operations. An excellent oil/water separation was obtained at T < 32 °C, at which the hydrophilic behavior was observed. The linear PNIPAm-grafted nylon membrane with 35% grafting yield had the highest separation efficiency of 99.7%, while PNIPAm structures were found to be independent of the separation efficiency. In addition, the membranes with thermoresponsive gas permeability were successfully achieved. The O2 and CO2 transmission rates through the PNIPAm-grafted nylon membranes decreased when the grafting yield increased, showing the better gas barrier property. The permeability ratio of CO2 to O2 transmission rates of both PNIPAm architectures at 25 °C and 35 °C were around 0.85 for low grafting yields, and approximately 1 for high grafting yields. Ultimately, this study demonstrated the possibility of using these thermoresponsive smart membranes in various applications.

Recently, groundwater resources have become the main freshwater supply for human activities worldwide, especially in semi-arid regions, and groundwater pollution from anthropological events is one of the chief environmental problems in built-up and industrial coastal areas. Many researchers around the world have conducted studies to evaluate the impact of groundwater management. For this study, GIS based GOD vulnerability models were used to assess the intrinsic impact and risk of pollution of coastal and irrigated areas in Tiruchendur Taluk, Thoothukudi district in Tamil Nadu. Here, GOD stands for G—Groundwater hydraulic confinement, O—Overlying aquifer strata, and D—Depth to groundwater. The parameters of G, O, and D show that 70% of the study area consists of an unconfined aquifer whose central part often consists of sandstone and fine to medium clay with sand along the coast that acts as an aquifer. The recorded value was 1–28 mbgl. The map of vulnerability using the GOD method shows that 32% of the medium vulnerabilities are located in the almost northern part of the study area, where the main source of pollution is from agricultural land and anthropological activities. A total of 39 groundwater samples were collected from different types of aquifers and used to validate the pollution map, using the EC concentration (230 to 15,480 µs/cm with an average of 2758 µs/cm) and NO3− concentration (2 to 120 mg/L with an average of 46 mg/L) in groundwater as indicators of pollution. Finally, we measured how the EC and NO3− parameters represent the medium vulnerability zone of the GOD model based on the pattern of their concentrations in groundwater. Therefore, the GIS with GOD model is the best model among these models for predicting groundwater vulnerability in Tiruchendur Taluk.

Introduction: Intestinal roundworms cause chronic debilitating disease in animals, including humans. Traditional experimental models of these types of infection use a large single-dose infection. However, in natural settings, hosts are exposed to parasites on a regular basis and when mice are exposed to frequent, smaller doses of Heligmosomoides polygyrus, the parasites are cleared more quickly. Whether this more effective host response has any negative consequences for the host is not known. Results: Using a trickle model of infection, we found that worm clearance was associated with known resistance-related host responses: increased granuloma and tuft cell numbers, increased levels of granuloma IgG and decreased intestinal transit time, as well as higher serum IgE levels. However, we found that the improved worm clearance was also associated with an inflammatory phenotype in and around the granuloma, increased smooth muscle hypertrophy/ hyperplasia, and elevated levels of Adamts gene expression. Discussion: To our knowledge, we are the first to identify the involvement of this protein family of matrix metalloproteinases (MMPs) in host responses to helminth infections. Our results highlight the delicate balance between parasite clearance and host tissue damage, which both contribute to host pathology. When continually exposed to parasitic worms, improved clearance comes at a cost. [ABSTRACT FROM AUTHOR]

Purpose: We report a dosimetric study in whole breast irradiation (WBI) of plan robustness evaluation against position error with two radiation techniques: tangential intensity-modulated radiotherapy (T-IMRT) and multi-angle IMRT (M-IMRT). Methods: Ten left-sided patients underwent WBI were selected. The dosimetric characteristics, biological evaluation and plan robustness were evaluated. The plan robustness quantification was performed by calculating the dose differences (Δ) of the original plan and perturbed plans, which were recalculated by introducing a 3-, 5-, and 10-mm shift in 18 directions. Results: M-IMRT showed better sparing of high-dose volume of organs at risk (OARs), but performed a larger low-dose irradiation volume of normal tissue. The greater shift worsened plan robustness. For a 10-mm perturbation, greater dose differences were observed in T-IMRT plans in nearly all directions, with higher Δ D 98%, Δ D 95%, and Δ D mean of CTV Boost and CTV. A 10-mm shift in inferior (I) direction induced CTV Boost in T-IMRT plans a 1.1 (Δ D 98%), 1.1 (Δ D 95%), and 1.7 (Δ D mean) times dose differences greater than dose differences in M-IMRT plans. For CTV Boost, shifts in the right (R) and I directions generated greater dose differences in T-IMRT plans, while shifts in left (L) and superior (S) directions generated larger dose differences in M-IMRT plans. For CTV, T-IMRT plans showed higher sensitivity to a shift in the R direction. M-IMRT plans showed higher sensitivity to shifts in L, S, and I directions. For OARs, negligible dose differences were found in V 20 of the lungs and heart. Greater Δ D max of the left anterior descending artery (LAD) was seen in M-IMRT plans. Conclusion: We proposed a plan robustness evaluation method to determine the beam angle against position uncertainty accompanied by optimal dose distribution and OAR sparing. [ABSTRACT FROM AUTHOR]

Musical cultural heritage, as an important component of cultural heritage, possesses significant cultural value and inheritance significance. With the development of society and the passage of time, these precious traditional musical cultural heritages inevitably face the dilemma of gradual depletion or even disappearance. In the digital age, effectively protecting and inheriting these musical cultural heritages has become an urgent problem to be addressed. Therefore, this paper proposes an application method based on digital twin technology, exploring how to protect and inherit musical cultural heritages through digital twin technology. By leveraging digital twin technology, a virtual museum dedicated to showcasing the richness and historical connotations of music cultures is created, preserving and simulating the soundscapes of historical music eras. Through the integration of audio archives, 3D modeling, and interactive displays, users can immerse themselves in the experience of historical music in the digital space. This paper evaluates the feasibility and cultural preservation value of this digital music history museum through the creation of music digital twin technology instances and user survey feedback and discusses the prospects of digital twins in the field of musical cultural heritage. [ABSTRACT FROM AUTHOR]

Physicochemical factors, plankton biomass, and sediment were measured from 1998 to 2000 at two months' interim in a eutrophic shoreline Lake, Hwajinpo, in Korea. The lake is isolated from the sea by a narrow sand hill. Coastal zone is well vegetated with floating leaved marine plants. The lake basin is divided into two sub-basins by a shallow ridge. It has disturbance of seawater by stormy waves. Stable chemoclines are made by salinity variations at depth of 1 m around the year. Dissolved Oxygen was often very low (<1 mgO2/L) at hypolimnion. Temperature reverse were detected in November. Nitrate and Ammonium concentrations were also very low (< 0.1 mgN/L), while TN was usually 2.0~3.5 mgN/L. In general, TN/TP was lower than the Redfield ratio. Transparency was 0.2~1.7m, and COD, TP, and TN of sediment were 3.1~40.3 mg O2/g, 0.91~1.39 mgP/g, and 0.34~3.07 mgN/g, respectively. Phytoplankton chlorophyll-a concentrations were mostly over 40 mg/m³. Two basins showed different phytoplankton groups with Oscillatoria sp., Trachelomonas sp., Schizochlamys gelatinosa, and Anabaena spiroides dominant in South basin, and with Trachelomonas sp., Schroederia sp., Schizochlamys gelatinosa, and Trachelomonas sp. dominant in the North basin. The seasonal progression of phytoplankton was quick, probably because of unexpected variations in physical environments, such as salinity, turbidity, wind, and light. [ABSTRACT FROM AUTHOR]

This study focuses on advancing the field of remote sensing image target detection, addressing challenges such as small target detection, complex background handling, and dense target distribution. We propose solutions based on enhancing the YOLOv7 algorithm. Firstly, we improve the multi-scale feature enhancement (MFE) method of YOLOv7, enhancing its adaptability and precision in detecting small targets and complex backgrounds. Secondly, we design a modified YOLOv7 global information DP-MLP module to effectively capture and integrate global information, thereby improving target detection accuracy and robustness, especially in handling large-scale variations and complex scenes. Lastly, we explore a semi-supervised learning model (SSLM) target detection algorithm incorporating unlabeled data, leveraging information from unlabeled data to enhance the model's generalization ability and performance. Experimental results demonstrate that despite the outstanding performance of YOLOv7, the mean average precision (MAP) can still be improved by 1.9%. Specifically, under testing on the TGRS-HRRSD-Dataset, the MFE and DP-MLP models achieve MAP values of 93.4% and 93.1%, respectively. Across the NWPU VHR-10 dataset, the three models achieve MAP values of 93.1%, 92.1%, and 92.2%, respectively. Significant improvements are observed across various metrics compared to the original model. This study enhances the adaptability, accuracy, and generalization of remote sensing image object detection. [ABSTRACT FROM AUTHOR]